Applying service levels to transcripts

ABSTRACT

Speech is transcribed to produce a draft transcript of the speech. Portions of the transcript having a high priority are identified. For example, particular sections of the transcript may be identified as high-priority sections. As another example, portions of the transcript requiring human verification may be identified as high-priority sections. High-priority portions of the transcript are verified at a first time, without verifying other portions of the transcript. Such other portions may or may not be verified at a later time. Limiting verification, either initially or entirely, to high-priority portions of the transcript limits the time required to perform such verification, thereby making it feasible to verify the most important portions of the transcript at an early stage without introducing an undue delay into the transcription process. Verifying the other portions of the transcript later ensures that early verification of the high-priority portions does not sacrifice overall verification accuracy.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Prov. Pat. App. Ser. No.60/815,689, filed on Jun. 22, 2006, entitled, “Verification of ExtractedFacts”; U.S. Prov. Pat. App. Ser. No. 60/815,688, filed on Jun. 22,2006, entitled, “Automatic Clinical Decision Support”; and U.S. Prov.Pat. App. Ser. No. 60/815/687, filed on Jun. 22, 2006, entitled, “DataExtraction Using Service Levels,” all of which are hereby incorporatedby reference herein.

This application is related to copending and commonly-owned U.S. patentapplication Ser. No. 10/923,517, filed on Aug. 20, 2004, entitled“Automated Extraction of Semantic Content and Generation of a StructuredDocument from Speech,” which is hereby incorporated by reference herein.

BACKGROUND

It is desirable in many contexts to generate a structured textualdocument based on human speech. In the legal profession, for example,transcriptionists transcribe testimony given in court proceedings and indepositions to produce a written transcript of the testimony. Similarly,in the medical profession, transcripts are produced of diagnoses,prognoses, prescriptions, and other information dictated by doctors andother medical professionals.

Producing such transcripts can be time-consuming. For example, the speedwith which a human transcriptionist can produce a transcript is limitedby the transcriptionist's typing speed and ability to understand thespeech being transcribed. Although software-based automatic speechrecognizers are often used to supplement or replace the role of thehuman transcriptionist in producing an initial transcript, even atranscript produced by a combination of human transcriptionist andautomatic speech recognizer will contain errors. Any transcript that isproduced, therefore, must be considered to be a draft, to which someform of error correction is to be applied.

Producing a transcript is time-consuming for these and other reasons.For example, it may be desirable or necessary for certain kinds oftranscripts (such as medical reports) to be stored and/or displayed in aparticular format. Providing a transcript in an appropriate formattypically requires some combination of human editing and automaticprocessing, which introduces an additional delay into the production ofthe final transcript.

Consumers of reports, such as doctors, nurses, and radiologists in themedical context, often stand to benefit from receiving reports quickly.If a diagnosis depends on the availability of a certain report, forexample, then the diagnosis cannot be provided until the required reportis ready. Similarly, if a doctor dictates a report of an operation intoa handheld dictation device while still in the operating room, it may bedesirable for a nurse to receive a transcript or other report of thedictation as soon as possible after the patient leaves the operatingroom. For these and other reasons it is desirable to increase the speedwith which transcripts and other kinds of reports derived from speechmay be produced, without sacrificing accuracy.

SUMMARY

Speech is transcribed to produce a draft transcript of the speech.Portions of the transcript having a high priority are identified. Forexample, particular sections of the transcript may be identified ashigh-priority sections. As another example, portions of the transcriptrequiring human verification may be identified as high-prioritysections. High-priority portions of the transcript are verified at afirst time, without verifying other portions of the transcript. Suchother portions may or may not be verified at a later time. Limitingverification, either initially or entirely, to high-priority portions ofthe transcript limits the time required to perform such verification,thereby making it feasible to verify the most important portions of thetranscript at an early stage without introducing an undue delay into thetranscription process. Verifying the other portions of the transcriptlater ensures that early verification of the high-priority portions doesnot sacrifice overall verification accuracy.

For example, one embodiment of the present invention is acomputer-implemented method comprising: (A) identifying a first semanticmeaning of a first portion of a first transcript of speech; (B)assigning a first service level to the first portion of the transcriptbased on the first semantic meaning; (C) identifying a second semanticmeaning of a second portion of the first transcript; (D) assigning asecond service level to the second portion of the transcript based onthe second semantic meaning; and (E) verifying the transcript inaccordance with the first and second service levels.

Another embodiment of the present invention is an apparatus comprising:first meaning identification means for identifying a first semanticmeaning of a first portion of a first transcript of speech; firstservice level assignment means for assigning a first service level tothe first portion of the transcript based on the first semantic meaning;second meaning identification means for identifying a second semanticmeaning of a second portion of the first transcript; second servicelevel assignment means for assigning a second service level to thesecond portion of the transcript based on the second semantic meaning;and verification means for verifying the transcript in accordance withthe first and second service levels.

Another embodiment of the present invention is a computer-implementedmethod comprising: (A) identifying a first semantic meaning of a firsttranscript of first speech; (B) assigning a first service level to thefirst transcript based on the first semantic meaning; (C) identifying asecond semantic meaning of a second transcript of second speech; (D)assigning a second service level to the second transcript based on thesecond semantic meaning; and (E) verifying the first and secondtranscripts in accordance with the first and second service levels,respectively.

Another embodiment of the present invention is an apparatus comprising:means for identifying a first semantic meaning of a first transcript offirst speech; means for assigning a first service level to the firsttranscript based on the first semantic meaning; means for identifying asecond semantic meaning of a second transcript of second speech; meansfor assigning a second service level to the second transcript based onthe second semantic meaning; and means for verifying the first andsecond transcripts in accordance with the first and second servicelevels, respectively.

Other features and advantages of various aspects and embodiments of thepresent invention will become apparent from the following descriptionand from the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a dataflow diagram of a system for verifying a transcript ofspeech according to one embodiment of the present invention; and

FIG. 2 is a flowchart of a method performed by the system of FIG. 1according to one embodiment of the present invention.

DETAILED DESCRIPTION

Embodiments of the invention are directed to verifying a transcript ofspeech using multiple service levels. Service levels may, for example,correspond to required turnaround times for verification. A “highpriority” service level may, for example, correspond to a relativelyshort turnaround time, while a “low priority” service level maycorrespond to another service level. As another example, the highpriority service level may indicate that human verification of thecorresponding text is required, while the low priority service level mayindicate that human verification is not required.

The priorities of different portions of a transcript are identified. Forexample, the “impressions” section of a medical transcript may beidentified as a high-priority section of the report, while othersections may be identified as low-priority sections. Verification ofeach portion of the document is performed according to that portion'sservice level. For example, high-priority sections (such as the“impressions” section) may be verified immediately, while low-prioritysections may be verified at a later time. As another example,high-priority sections may be verified by a human, while low-prioritysections may be verified by software or not at all.

More specifically, referring to FIG. 1, a dataflow diagram is shown of asystem 100 for selectively verifying portions of a draft transcript 106according to one embodiment of the present invention. Referring to FIG.2, a flowchart is shown of a method 200 performed by the system 100 ofFIG. 1 according to one embodiment of the present invention.

A transcription system 104 transcribes a spoken audio stream 102 toproduce a draft transcript 106 (step 202). The spoken audio stream 102may, for example, be dictation by a doctor describing a patient visit.The spoken audio stream 102 may take any form. For example, it may be alive audio stream received directly or indirectly (such as over atelephone or IP connection), or an audio stream recorded on any mediumand in any format.

The transcription system 104 may produce the draft transcript 106 using,for example, an automated speech recognizer or a combination of anautomated speech recognizer and human transcriptionist. Thetranscription system 104 may, for example, produce the draft transcript106 using any of the techniques disclosed in the above-referenced patentapplication entitled “Automated Extraction of Semantic Content andGeneration of a Structured Document from Speech.” As described therein,the draft transcript 106 may include text 116 that is either a literal(verbatim) transcript or a non-literal transcript of the spoken audiostream 102. As further described therein, although the draft transcript106 may be a plain text document, the draft transcript 106 may also, forexample, in whole or in part be a structured document, such as an XMLdocument which delineates document sections and other kinds of documentstructure. Various standards exist for encoding structured documents,and for annotating parts of the structured text with discrete facts(data) that are in some way related to the structured text. Examples ofexisting techniques for encoding medical documents include the HL7 CDAv2 XML standard (ANSI-approved since May 2005), SNOMED CT, LOINC, CPT,ICD-9 and ICD-10, and UMLS.

As shown in FIG. 1, the draft transcript 106 includes one or morecodings 108, each of which encodes a “concept” extracted from the spokenaudio stream 102. The term “concept” is used herein as defined in theabove-referenced patent application entitled “Automated Extraction ofSemantic content and Generation of a Structured Document from Speech.”Reference numeral 108 is used herein to refer generally to all of thecodings within the draft transcript 106. Although in FIG. 1 only twocodings, designated 108 a and 108 b, are shown, the draft transcript 106may include any number of codings.

In the context of a medical report, each of the codings 108 may, forexample, encode an allergy, prescription, diagnosis, or prognosis. Ingeneral, each of the codings 108 includes a code and corresponding data,which are not shown in FIG. 1 for ease of illustration. Each of thecodings 108 may be linked to text in the transcript 106. For example,coding 108 a may be linked to text 118 a and coding 108 b may be linkedto text 118 b. Assume for purposes of example that linked text 118 a isin a first section of the draft transcript 106 (such as an “impressions”section), and that linked text 118 b is in a second section of the drafttranscript 106 (such as a “patient history” section). Further details ofembodiments of the codings 108 may be found in the above-referencedpatent application entitled, “Verification of Data Extracted fromSpeech.”

A priority identifier 120 identifies verification priorities of one ormore portions of the draft transcript 106 to produce portion priorities122 (step 204). A “portion” of the draft transcript 106 may, forexample, be a single coding (such as the coding 108 a or coding 108 b),sentence, paragraph, or section.

In general, the priority identifier 120 identifies the priority of aportion of the draft transcript 106 by identifying a semantic meaning ofthe portion, and identifying the priority of the portion based on theidentified semantic meaning. For example, the priority identifier 120may be configured to assign a high priority to any “impressions”sections in the draft transcript 106 and a low priority to all othersections in the draft transcript 106.

As another example, certain portions of the draft transcript 106 mayrequire human (rather than software-based or other automated)verification. Typically, all portions of the draft transcript 106require human verification. Some portions, however, such as certaincodings representing data which are used solely for automatic computerprocessing, may not be rendered to the reviewer (e.g., physician) forreview and not require human verification. The priority identifier 120may be configured to assign a high priority to any portions of the drafttranscript 106 which require human verification, and to assign a lowpriority to all other portions of the draft transcript 106. The priorityidentifier 120 may identify portions of the draft transcript 106requiring human verification in any of a variety of ways. For example,the priority identifier 120 may be configured to identify certaincodings, or certain types of codings, as requiring human verification,in which case the priority identifier 120 may assign a high priority tosuch codings.

In general, the portions of the draft transcript 106 are verifiedaccording to service levels associated with their priorities (step 205).For example, a “high-priority” service level may be applied to portionsof the transcript 106 having a high priority. Similarly, a“low-priority” service level may be applied to portions of thetranscript 106 having a low priority. Since the priorities 122 of thedocument portions are identified based on the semantic meanings of theportions, the service levels that are applied to the portions are basedon the semantic meanings of the portions.

One example of applying such service levels is illustrated by steps206-212 in FIG. 2. More specifically, an initial transcript verifier 124verifies, at a first time, only those portions of the draft transcript106 which the priority identifier 120 has identified as having a highverification priority (step 206). The portion priorities 122 may, forexample, include links to the corresponding portions of the drafttranscript 106. The initial transcript verifier 124 may use such linksto identify which portions of the draft transcript 106 have highverification priorities and to verify only those portions of the drafttranscript 106. The initial transcript verifier 124 produces initialtranscript verification status identifiers 128 which indicate theverification status of each of the high-priority portions of the drafttranscript 106. A verification status may, for example, indicate whetherthe corresponding portion of the draft transcript 106 is correct orincorrect.

Any of a variety of techniques may be used to verify the high-priorityportions of the draft transcript 106, examples of which may be found inthe above-referenced patent application entitled, “Verification of DataExtracted from Speech.” For example, the high-priority portions of thedraft transcript 106 may be presented to a human reviewer, who may bethe same person who dictated the spoken audio stream. In fact, thespeaker of the spoken audio stream 102 may still be dictating theremainder of the spoken audio stream 102 while portions of the drafttranscript 106 representing previous parts of the spoken audio stream102 are presented to the reviewer for verification.

The verification process performed by the initial transcript verifier124 may include correcting any portions of the draft transcript 106 thatare found to be incorrect. For example, the reviewer may provide inputto correct one or more portions of the draft transcript 106 presentedfor review. The initial transcript verifier 124 may therefore produce amodified draft transcript 126, which includes any corrections to thecodings 108 or other modifications made by the initial transcriptverifier 124 (step 208).

Note that the initial transcript verification status identifiers 128 andthe modified draft transcript 126 may be combined. For example, portionsof the modified draft transcript 126 may be tagged with their ownverification statuses.

There is some delay 130 after the initial verification (step 210). Thedelay 130 may occur, for example, while the modified draft transcript126 is provided to a nurse or physician for use in providing medicalcare.

After the delay 130, a subsequent transcript verifier 132 verifiesportions of the modified draft transcript 126 other than those whichwere verified by the initial transcript verifier 124, thereby producinga final transcript 134 (step 212). For example, the subsequenttranscript verifier 132 may verify all of the portions which were notverified by the initial transcript verifier 124. The subsequenttranscript verifier 132 may use the same verification techniques as theinitial transcript verifier 124. Note that although the initialtranscript verifier 124 and subsequent transcript verifier 132 areillustrated as two distinct components in FIG. 1, they may be integratedinto a single component (e.g., a single software program).

The techniques just described may be viewed as implementing two tiers of“service level,” in which each tier corresponds to a differentturnaround time requirement. The first (high-priority) tier of servicelevel corresponds to a relatively short turnaround time, and the second(low-priority) tier of service level corresponds to a relatively longturnaround time. The priorities 122 assigned to portions of the drafttranscript 106 may, however, be used to implement service levelscorresponding to characteristics other than turnaround times.

For example, a first tier of service level may require the correspondingportion of the draft transcript 106 to be verified by a human, while asecond tier of service level may not require human verification. Forexample, the second tier may require software verification or notrequire any verification. In this example, the method of FIG. 2 wouldinclude only steps 202-208. More specifically, step 202 would includetranscribing the spoken audio stream to produce the draft transcript106, as described above. Step 204 would include identifying priorities122 of portions of the draft transcript 106. In this example, a highpriority would indicate that human verification is required, while a lowpriority would indicate that human verification is not required.

Step 206 would include verifying only those portions of the drafttranscript 106 having high priorities (i.e., only those portions of thedraft transcript 106 requiring human verification). Such verificationmay, for example, be performed by providing the draft transcript 106 toa human reviewer (such as the dictating physician) for review.

The method 200 would then terminate, without verifying the low-priorityportions of the draft transcript 106 because such portions have beenidentified as not requiring human verification. In yet anotherembodiment, a high service level would require verification by thedictating physician, a medium service level would require verificationby a data entry clerk, and a low service level would not require anyhuman verification.

Embodiments of the present invention have a variety of advantages. Forexample, transcripts of physician-dictated reports typically are notprovided to nurses and others for use in patient care soon after a draftof the transcript has been produced because it has not been possible toverify the accuracy of the transcript quickly enough. As a result, drafttranscripts typically are withheld until they have been verified, whichcan introduce a significant delay before such transcripts may be used.

One benefit of the techniques disclosed herein is that they make itpossible to provide transcripts to consumers of such transcripts bothquickly and with increased accuracy by limiting the amount of thetranscript that is verified, at least at the outset. In particular, bylimiting the verification, either initially or entirely, tohigh-priority portions of the draft transcript 106, the techniquesillustrated in FIGS. 1 and 2 increase the accuracy of those portions ofthe draft transcript 106 for which accuracy is most critical, withoutintroducing the significant delay that would otherwise be incurred byverifying the entire transcript.

Furthermore, the techniques disclosed herein do not create significantadditional work for the physician or other dictator/reviewer of thetranscript, and may thereby reduce the total amount of time they need todevote to performing their tasks. If, for example, the initialtranscript verifier 124 presents high-priority portions of the drafttranscript 106 to a physician for review immediately after the physiciandictates such portions, or even while the physician is dictating suchportions, the physician may verify and correct any errors in suchportions more efficiently than if those portions of the transcript wereprovided to the physician for review an hour, day, or week later becauseof the switching costs involved. Furthermore, overall accuracy may beincreased because the dictator/reviewer of the draft transcript 106 mayhave a clearer memory of the intended content of the draft transcript106 is presented to him or her immediately after dictating it, ratherthan at a later time.

These techniques are particularly useful in contexts in which atranscript needs to be made available immediately to someone other thanthe dictator of the transcript. For example, the “impressions” sectionof a radiology report needs to be made available immediately foremergency room radiology studies, while the rest of the document may becompleted at a later time. In order to guarantee immediate turnaround,the “impressions” section of the draft transcript 106 may be provided tothe dictating physician immediately for self-correction, while leavingthe remainder of the document to be corrected at a later time byprofessional transcriptionists.

As another example, the medication and allergy sections of a progressnote may be interpreted and populated immediately in an electronicmedical records (EMR) system to be available for order entry (i.e.,prescription medications) and decision support at point of care. Otherdata elements (e.g., history of present illness) may be verified at alater time.

Another benefit of techniques disclosed herein is that they may becombined with the techniques disclosed in the above-referenced patentapplication entitled “Automatic Decision Support” for applying automatedclinical decision support to transcripts. For example, the modifieddraft transcript 126 may be provided to an automated clinical decisionsupport system, as described in the above-referenced patent application,to provide clinical decision support quickly. Such techniques may, forexample, be used to provide a quick indication of whether the drafttranscript 126 indicates a dangerous drug-drug allergy which requiresattention by the dictating physician or other care provider. Thetechniques disclosed herein facilitate the provision of such rapidclinical decision support by enabling verification of high-priorityportions of the draft transcript 106 to be performed soon after thedraft transcript 106 is produced. If verification of such high-priorityportions had to wait until all portions of the draft transcript 106 wereverified, then application of automated clinical decision support to thehigh-priority portions would have to wait as well.

In this regard, portions of the draft transcript 106 which are necessaryto provide as input a clinical decision support system may be assigned ahigh priority. As a result, the initial transcript verifier 124 willverify those portions of the draft transcript 106 which are necessary toprovide as input to the clinical decision support system. This ensuresthat any desired clinical decision support can be applied to themodified draft transcript 126 produced by the initial transcriptverifier 124, without incurring additional delay.

It is to be understood that although the invention has been describedabove in terms of particular embodiments, the foregoing embodiments areprovided as illustrative only, and do not limit or define the scope ofthe invention. Various other embodiments, including but not limited tothe following, are also within the scope of the claims. For example,elements and components described herein may be further divided intoadditional components or joined together to form fewer components forperforming the same functions.

Although certain examples provided herein involve documents generated bya speech recognizer, this is not a requirement of the present invention.Rather, the techniques disclosed herein may be applied to any kind ofdocument, regardless of how it was generated. Such techniques may, forexample, be used in conjunction with documents typed using conventionaltext editors.

The spoken audio stream 102 may be any audio stream, such as a liveaudio stream received directly or indirectly (such as over a telephoneor IP connection), or an audio stream recorded on any medium and in anyformat. In distributed speech recognition (DSR), a client performspreprocessing on an audio stream to produce a processed audio streamthat is transmitted to a server, which performs speech recognition onthe processed audio stream. The audio stream may, for example, be aprocessed audio stream produced by a DSR client.

The invention is not limited to any of the described domains (such asthe medical and legal fields), but generally applies to any kind ofdocuments in any domain. For example, although the reviewer 138 may bedescribed herein as a physician, this is not a limitation of the presentinvention. Rather, the reviewer 138 may be any person. Furthermore,documents used in conjunction with embodiments of the present inventionmay be represented in any machine-readable form. Such forms includeplain text documents and structured documents represented in markuplanguages such as XML. Such documents may be stored in anycomputer-readable medium and transmitted using any kind ofcommunications channel and protocol.

Although certain examples described herein include only twopriorities—high and low—these are merely examples of priorities and donot constitute limitations of the present invention. Rather, thetechniques disclosed herein may be applied to any number of prioritiesdefined and/or labeled in any manner. For example, there may be high,medium, and low priorities. As another examples, priorities may specifymaximum turnaround times, such as one minute, one hour, and one day.

Furthermore, although in certain examples herein the high priorityservice level is described as providing “immediate” verification, thisis not a requirement of the present invention. Rather, service levelsmay be defined and applied in any manner. For example, even when servicelevels define turnaround requirements, the highest-priority servicelevel need not require immediate turnaround, but rather may require orallow any amount of delay.

Although certain examples disclosed herein apply different servicelevels to different portions of a single transcript, the same or similartechniques may be used to apply different service levels to differentdocuments. In other words, a first (e.g., high-priority) service levelmay be applied to a first entire document and a second (e.g.,low-priority) service level may be applied to a second entire document.The first and second documents may then be verified in accordance withtheir respective service levels.

For example, the transcription system 104 may transcribe a first spokenaudio stream to produce a first draft transcript and apply automaticdecision support to the first draft transcript using the techniquesdisclosed in the above-referenced patent application entitled,“Automatic Decision Support.” A first service level may be associatedwith the first draft transcript based on the results of the automaticdecision support. For example, if automatic decision support determinesthat the draft transcript does not include any critical errors, then alow-priority service level may be associated with the first drafttranscript.

The transcription system 104 may also transcribe a second spoken audiostream to produce a second draft transcript and apply automatic decisionsupport to the second draft transcript using the above-describedtechniques. A second service level may be associated with the seconddraft transcript based on the results of the automatic decision support.For example, if automatic decision support determines that the seconddraft transcript contains a critical error (such as by describing aprescription that would result in a drug-drug allergy), then ahigh-priority service level may be associated with the second drafttranscript.

The first and second draft transcripts may then be verified inaccordance with their respective service levels. For example, the seconddraft transcript may be presented for verification before the firstdraft transcript, even though the first draft transcript was transcribedbefore the second draft transcript, because the second draft transcriptis associated with a higher service level than the first drafttranscript. As one example of processing the two draft transcripts inaccordance with their respective service levels, a phone call might bemade immediately to the dictating physician of the second drafttranscript to alert him or her to the identified error. As anotherexample, the second draft transcript might be placed at the top of thequeue of documents to which full verification is to be applied. Ineither case, the (low-priority) first draft transcript may be verifiedat a later time. Such application of different service levels todifferent documents shares benefits of the techniques disclosed hereinfor applying different service levels to different portions of a singledocument.

Although the verification statuses 130 may include statuses such as“correct” and “incorrect,” the invention is not so limited. Rather, theverification statuses 130 may take any of a variety of forms. Furtherexamples of the verification statuses and techniques for producing themmay be found in the above-referenced patent application entitled,“Verification of Extracted Data.”

Although certain individual types of service levels are describedherein, such service levels are merely examples and do not constitutelimitations of the present invention. For example, the above-referencedpatent application entitled, “Automatic Decision Support,” disclosestechniques for performing real-time automatic decision support, in whichdecision support is applied to a transcript-in-progress while thephysician (or other speaker) is still dictating the report. If thedecision support system identifies a critical error or other problemrequiring the immediate attention of the speaker-reviewer, the systemnotifies the speaker-reviewer of the problem while the report is stillbeing dictated. Such immediate, real-time presentation of a partialtranscript for review may be viewed as a service level, in comparison,for example, to service levels in which lower-priority errors are notdeferred until dictation of the report is complete.

Furthermore, service levels not disclosed herein may be used inconjunction with the techniques disclosed herein. Furthermore, servicelevels may be combined with each other in various ways. For example, a“high-priority” service level may be applied to any portions of thedraft transcript 106 which: (1) are within predetermined sections of thetranscript 106; or (2) which require human verification.

The verification performed by the initial transcript verifier 124 andthe subsequent transcript verifier 132 may be performed in whole or inpart by a human, such as the dictator of the draft transcript 106. Tofacilitate such verification, the high-priority portions of the drafttranscript 106 may be called out to the reviewer, such as byhighlighting them or displaying them in a different color within adisplay of the draft transcript 106. Such a display may, for example, bedisplayed to the reviewer while the reviewer is dictating the contentsof the transcript 106.

The techniques described above may be implemented, for example, inhardware, software, firmware, or any combination thereof. The techniquesdescribed above may be implemented in one or more computer programsexecuting on a programmable computer including a processor, a storagemedium readable by the processor (including, for example, volatile andnon-volatile memory and/or storage elements), at least one input device,and at least one output device. Program code may be applied to inputentered using the input device to perform the functions described and togenerate output. The output may be provided to one or more outputdevices.

Each computer program within the scope of the claims below may beimplemented in any programming language, such as assembly language,machine language, a high-level procedural programming language, or anobject-oriented programming language. The programming language may, forexample, be a compiled or interpreted programming language.

Each such computer program may be implemented in a computer programproduct tangibly embodied in a machine-readable storage device forexecution by a computer processor. Method steps of the invention may beperformed by a computer processor executing a program tangibly embodiedon a computer-readable medium to perform functions of the invention byoperating on input and generating output. Suitable processors include,by way of example, both general and special purpose microprocessors.Generally, the processor receives instructions and data from a read-onlymemory and/or a random access memory. Storage devices suitable fortangibly embodying computer program instructions include, for example,all forms of non-volatile memory, such as semiconductor memory devices,including EPROM, EEPROM, and flash memory devices; magnetic disks suchas internal hard disks and removable disks; magneto-optical disks; andCD-ROMs. Any of the foregoing may be supplemented by, or incorporatedin, specially-designed ASICs (application-specific integrated circuits)or FPGAs (Field-Programmable Gate Arrays). A computer can generally alsoreceive programs and data from a storage medium such as an internal disk(not shown) or a removable disk. These elements will also be found in aconventional desktop or workstation computer as well as other computerssuitable for executing computer programs implementing the methodsdescribed herein, which may be used in conjunction with any digitalprint engine or marking engine, display monitor, or other raster outputdevice capable of producing color or gray scale pixels on paper, film,display screen, or other output medium.

What is claimed is:
 1. A method performed by at least one computerprocessor executing computer program instructions stored on at least onenon-transitory computer-readable medium, the method comprising: (A)identifying a first semantic meaning of a first portion of a firsttranscript of speech; (B) assigning a first service level to the firstportion of the transcript based on the first semantic meaning; (C)identifying a second semantic meaning of a second portion of the firsttranscript; (D) assigning a second service level to the second portionof the transcript based on the second semantic meaning; and (E) at aprocessor verifying the transcript in accordance with the first andsecond service levels.
 2. The method of claim 1, wherein (E) comprises:(E)(1) verifying the first portion at a first time; and (E)(2) verifyingthe second portion at a second time that is later than the first time.3. The method of claim 1, wherein (A) comprises: (A)(1) identifying afirst plurality of semantic meanings of a first plurality of portions ofthe first transcript of speech; wherein (B) comprises: (B)(1) assigningthe first service level to the first plurality of portions of the firsttranscript; wherein (C) comprises: (C)(1) identifying a second pluralityof semantic meanings of a second plurality of portions of the firsttranscript; wherein (D) comprises: (D)(1) assigning the second servicelevel to the second plurality of portions of the first transcript; andand wherein (E) comprises: (E)(1) verifying the first plurality ofportions during a first time period; and (E)(2) verifying the secondplurality of portions during a second time period that is later than thefirst time period.
 4. The method of claim 1, wherein (E) comprises:(E)(1) verifying the first portion using a human verifier.
 5. The methodof claim 4, wherein (E) further comprises: (E)(2) verifying the secondportion using a computer-implemented verifier.
 6. The method of claim 1,wherein (A) comprises identifying a document section type of the firstportion of the first transcript, and wherein (B) comprises assigning thefirst service level to the first portion of the transcript based on thedocument section type.
 7. The method of claim 1, wherein (B) comprises:(B)(1) determining whether the first portion requires verification by ahuman; and (B)(2) assigning the first service level to the first portionbased on whether the first portion requires verification by a human. 8.An apparatus comprising at least one non-transitory computer-readablemedium having computer program instructions stored thereon, wherein thecomputer program instructions are executable by at least one computerprocessor to perform a method, the method comprising: (A) identifying afirst semantic meaning of a first portion of a first transcript ofspeech; (B) assigning a first service level to the first portion of thetranscript based on the first semantic meaning; (C) identifying a secondsemantic meaning of a second portion of the first transcript; (D)assigning a second service level to the second portion of the transcriptbased on the second semantic meaning; and (E) verifying the transcriptin accordance with the first and second service levels.
 9. The apparatusof claim 8, wherein (E) comprises: (E)(1) verifying the first portion ata first time; and (E)(2) verifying the second portion at a second timethat is later than the first time.
 10. The apparatus of claim 8, wherein(A) comprises identifying a document section type of the first portionof the first transcript, and wherein (B) comprises assigning the firstservice level to the first portion of the transcript based on thedocument section type.
 11. The apparatus of claim 8, wherein (B)comprises: (B)(1) determining whether the first portion requiresverification by a human; and (B)(2) assigning the first service level tothe first portion based on whether the first portion requiresverification by a human.
 12. A method performed by at least one computerprocessor executing computer program instructions stored on at least onenon-transitory computer-readable medium, the method comprising: (A)identifying a first semantic meaning of a first transcript of firstspeech; (B) assigning a first service level to the first transcriptbased on the first semantic meaning; (C) identifying a second semanticmeaning of a second transcript of second speech; (D) assigning a secondservice level to the second transcript based on the second semanticmeaning; and (E) at a processor verifying the first and secondtranscripts in accordance with the first and second service levels,respectively.
 13. An apparatus comprising at least one non-transitorycomputer-readable medium having computer program instructions storedthereon, wherein the computer program instructions are executable by atleast one computer processor to perform a method, the method comprising:(A) identifying a first semantic meaning of a first transcript of firstspeech; (B) assigning a first service level to the first transcriptbased on the first semantic meaning; (C) identifying a second semanticmeaning of a second transcript of second speech; (D) assigning a secondservice level to the second transcript based on the second semanticmeaning; and (E) verifying the first and second transcripts inaccordance with the first and second service levels, respectively.